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  <div class="section" id="torchvision">
<h1>torchvision<a class="headerlink" href="#torchvision" title="Permalink to this headline">¶</a></h1>
<p>The <a class="reference internal" href="#module-torchvision" title="torchvision"><code class="xref py py-mod docutils literal notranslate"><span class="pre">torchvision</span></code></a> package consists of popular datasets, model
architectures, and common image transformations for computer vision.</p>
<div class="toctree-wrapper compound">
<p class="caption"><span class="caption-text">Package Reference</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="datasets.html">torchvision.datasets</a><ul>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#mnist">MNIST</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#fashion-mnist">Fashion-MNIST</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#kmnist">KMNIST</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#emnist">EMNIST</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#qmnist">QMNIST</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#fakedata">FakeData</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#coco">COCO</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#lsun">LSUN</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#imagefolder">ImageFolder</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#datasetfolder">DatasetFolder</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#imagenet">ImageNet</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#cifar">CIFAR</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#stl10">STL10</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#svhn">SVHN</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#phototour">PhotoTour</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#sbu">SBU</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#flickr">Flickr</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#voc">VOC</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#cityscapes">Cityscapes</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#sbd">SBD</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#usps">USPS</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#kinetics-400">Kinetics-400</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#hmdb51">HMDB51</a></li>
<li class="toctree-l2"><a class="reference internal" href="datasets.html#ucf101">UCF101</a></li>
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<li class="toctree-l2"><a class="reference internal" href="io.html#video">Video</a></li>
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<li class="toctree-l2"><a class="reference internal" href="models.html#classification">Classification</a></li>
<li class="toctree-l2"><a class="reference internal" href="models.html#semantic-segmentation">Semantic Segmentation</a></li>
<li class="toctree-l2"><a class="reference internal" href="models.html#object-detection-instance-segmentation-and-person-keypoint-detection">Object Detection, Instance Segmentation and Person Keypoint Detection</a></li>
<li class="toctree-l2"><a class="reference internal" href="models.html#video-classification">Video classification</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="ops.html">torchvision.ops</a></li>
<li class="toctree-l1"><a class="reference internal" href="transforms.html">torchvision.transforms</a><ul>
<li class="toctree-l2"><a class="reference internal" href="transforms.html#transforms-on-pil-image">Transforms on PIL Image</a></li>
<li class="toctree-l2"><a class="reference internal" href="transforms.html#transforms-on-torch-tensor">Transforms on torch.*Tensor</a></li>
<li class="toctree-l2"><a class="reference internal" href="transforms.html#conversion-transforms">Conversion Transforms</a></li>
<li class="toctree-l2"><a class="reference internal" href="transforms.html#generic-transforms">Generic Transforms</a></li>
<li class="toctree-l2"><a class="reference internal" href="transforms.html#functional-transforms">Functional Transforms</a></li>
</ul>
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<li class="toctree-l1"><a class="reference internal" href="utils.html">torchvision.utils</a></li>
</ul>
</div>
<span class="target" id="module-torchvision"></span><dl class="function">
<dt id="torchvision.get_image_backend">
<code class="descclassname">torchvision.</code><code class="descname">get_image_backend</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/torchvision.html#get_image_backend"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torchvision.get_image_backend" title="Permalink to this definition">¶</a></dt>
<dd><p>Gets the name of the package used to load images</p>
</dd></dl>

<dl class="function">
<dt id="torchvision.set_image_backend">
<code class="descclassname">torchvision.</code><code class="descname">set_image_backend</code><span class="sig-paren">(</span><em>backend</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torchvision.html#set_image_backend"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torchvision.set_image_backend" title="Permalink to this definition">¶</a></dt>
<dd><p>Specifies the package used to load images.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>backend</strong> (<em>string</em>) – Name of the image backend. one of {‘PIL’, ‘accimage’}.
The <code class="xref py py-mod docutils literal notranslate"><span class="pre">accimage</span></code> package uses the Intel IPP library. It is
generally faster than PIL, but does not support as many operations.</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="torchvision.set_video_backend">
<code class="descclassname">torchvision.</code><code class="descname">set_video_backend</code><span class="sig-paren">(</span><em>backend</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torchvision.html#set_video_backend"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torchvision.set_video_backend" title="Permalink to this definition">¶</a></dt>
<dd><p>Specifies the package used to decode videos.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>backend</strong> (<em>string</em>) – Name of the video backend. one of {‘pyav’, ‘video_reader’}.
The <code class="xref py py-mod docutils literal notranslate"><span class="pre">pyav</span></code> package uses the 3rd party PyAv library. It is a Pythonic
binding for the FFmpeg libraries.
The <code class="xref py py-mod docutils literal notranslate"><span class="pre">video_reader</span></code> package includes a native C++ implementation on
top of FFMPEG libraries, and a python API of TorchScript custom operator.
It is generally decoding faster than <code class="xref py py-mod docutils literal notranslate"><span class="pre">pyav</span></code>, but perhaps is less robust.</td>
</tr>
</tbody>
</table>
</dd></dl>

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